R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(1217
+ ,1210
+ ,0
+ ,31.00
+ ,48
+ ,961.00
+ ,2304
+ ,1202
+ ,1209
+ ,0
+ ,34.40
+ ,38
+ ,1183.36
+ ,1444
+ ,1180
+ ,1207
+ ,0
+ ,35.60
+ ,37
+ ,1267.36
+ ,1369
+ ,1167
+ ,1206
+ ,0
+ ,32.80
+ ,48
+ ,1075.84
+ ,2304
+ ,1186
+ ,1204
+ ,1
+ ,23.30
+ ,81
+ ,542.89
+ ,6561
+ ,1168
+ ,1201
+ ,1
+ ,20.00
+ ,58
+ ,400.00
+ ,3364
+ ,1142
+ ,1199
+ ,1
+ ,16.70
+ ,93
+ ,278.89
+ ,8649
+ ,1147
+ ,1198
+ ,0
+ ,17.80
+ ,86
+ ,316.84
+ ,7396
+ ,1183
+ ,1196
+ ,0
+ ,21.20
+ ,68
+ ,449.44
+ ,4624
+ ,1149
+ ,1195
+ ,0
+ ,23.90
+ ,68
+ ,571.21
+ ,4624
+ ,1197
+ ,1193
+ ,0
+ ,28.80
+ ,68
+ ,829.44
+ ,4624
+ ,1210
+ ,1191
+ ,0
+ ,25.60
+ ,59
+ ,655.36
+ ,3481
+ ,1206
+ ,1190
+ ,0
+ ,29.40
+ ,43
+ ,864.36
+ ,1849
+ ,1196
+ ,1188
+ ,0
+ ,22.80
+ ,59
+ ,519.84
+ ,3481
+ ,1190
+ ,1187
+ ,0
+ ,16.10
+ ,31
+ ,259.21
+ ,961
+ ,1175
+ ,1185
+ ,0
+ ,16.10
+ ,49
+ ,259.21
+ ,2401
+ ,1186
+ ,1183
+ ,0
+ ,20.00
+ ,52
+ ,400.00
+ ,2704
+ ,1172
+ ,1182
+ ,0
+ ,20.60
+ ,75
+ ,424.36
+ ,5625
+ ,1152
+ ,1185
+ ,1
+ ,18.30
+ ,90
+ ,334.89
+ ,8100
+ ,1154
+ ,1179
+ ,1
+ ,21.60
+ ,86
+ ,466.56
+ ,7396
+ ,1168
+ ,1177
+ ,0
+ ,22.80
+ ,87
+ ,519.84
+ ,7569
+ ,1180
+ ,1175
+ ,0
+ ,22.80
+ ,47
+ ,519.84
+ ,2209
+ ,1169
+ ,1174
+ ,0
+ ,17.20
+ ,70
+ ,295.84
+ ,4900
+ ,1166
+ ,1170
+ ,0
+ ,22.20
+ ,61
+ ,492.84
+ ,3721
+ ,1177
+ ,1169
+ ,0
+ ,20.60
+ ,48
+ ,424.36
+ ,2304
+ ,1168
+ ,1167
+ ,0
+ ,18.30
+ ,67
+ ,334.89
+ ,4489
+ ,1160
+ ,1166
+ ,0
+ ,16.70
+ ,74
+ ,278.89
+ ,5476
+ ,1147
+ ,1164
+ ,1
+ ,22.80
+ ,55
+ ,519.84
+ ,3025
+ ,1161
+ ,1162
+ ,0
+ ,13.90
+ ,47
+ ,193.21
+ ,2209
+ ,1143
+ ,1161
+ ,0
+ ,10.00
+ ,65
+ ,100.00
+ ,4225
+ ,1161
+ ,1159
+ ,0
+ ,16.10
+ ,28
+ ,259.21
+ ,784
+ ,1161
+ ,1158
+ ,0
+ ,20.60
+ ,30
+ ,424.36
+ ,900
+ ,1168
+ ,1156
+ ,0
+ ,19.40
+ ,67
+ ,376.36
+ ,4489
+ ,1172
+ ,1155
+ ,0
+ ,25.60
+ ,32
+ ,655.36
+ ,1024)
+ ,dim=c(7
+ ,34)
+ ,dimnames=list(c('Time'
+ ,'Sunset'
+ ,'Rain'
+ ,'T'
+ ,'H'
+ ,'T^2'
+ ,'H^2')
+ ,1:34))
> y <- array(NA,dim=c(7,34),dimnames=list(c('Time','Sunset','Rain','T','H','T^2','H^2'),1:34))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Time Sunset Rain T H T^2 H^2
1 1217 1210 0 31.0 48 961.00 2304
2 1202 1209 0 34.4 38 1183.36 1444
3 1180 1207 0 35.6 37 1267.36 1369
4 1167 1206 0 32.8 48 1075.84 2304
5 1186 1204 1 23.3 81 542.89 6561
6 1168 1201 1 20.0 58 400.00 3364
7 1142 1199 1 16.7 93 278.89 8649
8 1147 1198 0 17.8 86 316.84 7396
9 1183 1196 0 21.2 68 449.44 4624
10 1149 1195 0 23.9 68 571.21 4624
11 1197 1193 0 28.8 68 829.44 4624
12 1210 1191 0 25.6 59 655.36 3481
13 1206 1190 0 29.4 43 864.36 1849
14 1196 1188 0 22.8 59 519.84 3481
15 1190 1187 0 16.1 31 259.21 961
16 1175 1185 0 16.1 49 259.21 2401
17 1186 1183 0 20.0 52 400.00 2704
18 1172 1182 0 20.6 75 424.36 5625
19 1152 1185 1 18.3 90 334.89 8100
20 1154 1179 1 21.6 86 466.56 7396
21 1168 1177 0 22.8 87 519.84 7569
22 1180 1175 0 22.8 47 519.84 2209
23 1169 1174 0 17.2 70 295.84 4900
24 1166 1170 0 22.2 61 492.84 3721
25 1177 1169 0 20.6 48 424.36 2304
26 1168 1167 0 18.3 67 334.89 4489
27 1160 1166 0 16.7 74 278.89 5476
28 1147 1164 1 22.8 55 519.84 3025
29 1161 1162 0 13.9 47 193.21 2209
30 1143 1161 0 10.0 65 100.00 4225
31 1161 1159 0 16.1 28 259.21 784
32 1161 1158 0 20.6 30 424.36 900
33 1168 1156 0 19.4 67 376.36 4489
34 1172 1155 0 25.6 32 655.36 1024
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Sunset Rain T H `T^2`
471.725413 0.524500 -13.466945 6.334415 0.710215 -0.121688
`H^2`
-0.009109
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-37.562 -3.797 2.096 6.719 20.988
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 471.725413 235.339505 2.004 0.0551 .
Sunset 0.524500 0.199890 2.624 0.0141 *
Rain -13.466945 7.495860 -1.797 0.0836 .
T 6.334415 2.735829 2.315 0.0284 *
H 0.710215 0.869048 0.817 0.4209
`T^2` -0.121688 0.059559 -2.043 0.0509 .
`H^2` -0.009109 0.007281 -1.251 0.2216
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 13.77 on 27 degrees of freedom
Multiple R-squared: 0.5931, Adjusted R-squared: 0.5027
F-statistic: 6.56 on 6 and 27 DF, p-value: 0.0002321
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.9979120 4.175970e-03 2.087985e-03
[2,] 0.9999732 5.362586e-05 2.681293e-05
[3,] 0.9999844 3.122885e-05 1.561443e-05
[4,] 0.9999747 5.051504e-05 2.525752e-05
[5,] 0.9999688 6.231351e-05 3.115675e-05
[6,] 0.9999665 6.691456e-05 3.345728e-05
[7,] 0.9999295 1.410622e-04 7.053111e-05
[8,] 0.9998570 2.859532e-04 1.429766e-04
[9,] 0.9995198 9.604210e-04 4.802105e-04
[10,] 0.9984708 3.058380e-03 1.529190e-03
[11,] 0.9981555 3.689000e-03 1.844500e-03
[12,] 0.9942359 1.152812e-02 5.764059e-03
[13,] 0.9866378 2.672444e-02 1.336222e-02
[14,] 0.9741710 5.165804e-02 2.582902e-02
[15,] 0.9746170 5.076608e-02 2.538304e-02
> postscript(file="/var/wessaorg/rcomp/tmp/1x8dp1331157295.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2c5q71331157295.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/32ico1331157295.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/435nc1331157295.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5n1it1331157295.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 34
Frequency = 1
1 2 3 4 5 6
18.1012211 8.4160626 -9.8873387 -27.2280228 16.9494537 -8.7469694
7 8 9 10 11 12
-4.2503658 -20.9842315 -1.8016777 -37.5620942 11.8718837 20.9882259
13 14 15 16 17 18
15.3729513 9.8068680 11.9884935 -1.6299130 3.4766648 -0.5637139
19 20 21 22 23 24
6.9021182 3.5966348 4.9265359 -2.4382606 3.4771961 -9.4714221
25 26 27 28 29 30
0.1807460 2.3197621 2.1835110 -14.4508716 2.0094320 3.4747490
31 32 33 34
-1.8070902 -10.0544343 6.1678273 -1.3339314
> postscript(file="/var/wessaorg/rcomp/tmp/62dop1331157295.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 34
Frequency = 1
lag(myerror, k = 1) myerror
0 18.1012211 NA
1 8.4160626 18.1012211
2 -9.8873387 8.4160626
3 -27.2280228 -9.8873387
4 16.9494537 -27.2280228
5 -8.7469694 16.9494537
6 -4.2503658 -8.7469694
7 -20.9842315 -4.2503658
8 -1.8016777 -20.9842315
9 -37.5620942 -1.8016777
10 11.8718837 -37.5620942
11 20.9882259 11.8718837
12 15.3729513 20.9882259
13 9.8068680 15.3729513
14 11.9884935 9.8068680
15 -1.6299130 11.9884935
16 3.4766648 -1.6299130
17 -0.5637139 3.4766648
18 6.9021182 -0.5637139
19 3.5966348 6.9021182
20 4.9265359 3.5966348
21 -2.4382606 4.9265359
22 3.4771961 -2.4382606
23 -9.4714221 3.4771961
24 0.1807460 -9.4714221
25 2.3197621 0.1807460
26 2.1835110 2.3197621
27 -14.4508716 2.1835110
28 2.0094320 -14.4508716
29 3.4747490 2.0094320
30 -1.8070902 3.4747490
31 -10.0544343 -1.8070902
32 6.1678273 -10.0544343
33 -1.3339314 6.1678273
34 NA -1.3339314
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 8.4160626 18.1012211
[2,] -9.8873387 8.4160626
[3,] -27.2280228 -9.8873387
[4,] 16.9494537 -27.2280228
[5,] -8.7469694 16.9494537
[6,] -4.2503658 -8.7469694
[7,] -20.9842315 -4.2503658
[8,] -1.8016777 -20.9842315
[9,] -37.5620942 -1.8016777
[10,] 11.8718837 -37.5620942
[11,] 20.9882259 11.8718837
[12,] 15.3729513 20.9882259
[13,] 9.8068680 15.3729513
[14,] 11.9884935 9.8068680
[15,] -1.6299130 11.9884935
[16,] 3.4766648 -1.6299130
[17,] -0.5637139 3.4766648
[18,] 6.9021182 -0.5637139
[19,] 3.5966348 6.9021182
[20,] 4.9265359 3.5966348
[21,] -2.4382606 4.9265359
[22,] 3.4771961 -2.4382606
[23,] -9.4714221 3.4771961
[24,] 0.1807460 -9.4714221
[25,] 2.3197621 0.1807460
[26,] 2.1835110 2.3197621
[27,] -14.4508716 2.1835110
[28,] 2.0094320 -14.4508716
[29,] 3.4747490 2.0094320
[30,] -1.8070902 3.4747490
[31,] -10.0544343 -1.8070902
[32,] 6.1678273 -10.0544343
[33,] -1.3339314 6.1678273
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 8.4160626 18.1012211
2 -9.8873387 8.4160626
3 -27.2280228 -9.8873387
4 16.9494537 -27.2280228
5 -8.7469694 16.9494537
6 -4.2503658 -8.7469694
7 -20.9842315 -4.2503658
8 -1.8016777 -20.9842315
9 -37.5620942 -1.8016777
10 11.8718837 -37.5620942
11 20.9882259 11.8718837
12 15.3729513 20.9882259
13 9.8068680 15.3729513
14 11.9884935 9.8068680
15 -1.6299130 11.9884935
16 3.4766648 -1.6299130
17 -0.5637139 3.4766648
18 6.9021182 -0.5637139
19 3.5966348 6.9021182
20 4.9265359 3.5966348
21 -2.4382606 4.9265359
22 3.4771961 -2.4382606
23 -9.4714221 3.4771961
24 0.1807460 -9.4714221
25 2.3197621 0.1807460
26 2.1835110 2.3197621
27 -14.4508716 2.1835110
28 2.0094320 -14.4508716
29 3.4747490 2.0094320
30 -1.8070902 3.4747490
31 -10.0544343 -1.8070902
32 6.1678273 -10.0544343
33 -1.3339314 6.1678273
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/70qhd1331157295.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8o4pl1331157295.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9c3bp1331157295.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/1091wb1331157295.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11k80n1331157295.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12dnz11331157295.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13pivs1331157295.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/14vjhv1331157295.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/159z9x1331157295.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/163yjg1331157295.tab")
+ }
>
> try(system("convert tmp/1x8dp1331157295.ps tmp/1x8dp1331157295.png",intern=TRUE))
character(0)
> try(system("convert tmp/2c5q71331157295.ps tmp/2c5q71331157295.png",intern=TRUE))
character(0)
> try(system("convert tmp/32ico1331157295.ps tmp/32ico1331157295.png",intern=TRUE))
character(0)
> try(system("convert tmp/435nc1331157295.ps tmp/435nc1331157295.png",intern=TRUE))
character(0)
> try(system("convert tmp/5n1it1331157295.ps tmp/5n1it1331157295.png",intern=TRUE))
character(0)
> try(system("convert tmp/62dop1331157295.ps tmp/62dop1331157295.png",intern=TRUE))
character(0)
> try(system("convert tmp/70qhd1331157295.ps tmp/70qhd1331157295.png",intern=TRUE))
character(0)
> try(system("convert tmp/8o4pl1331157295.ps tmp/8o4pl1331157295.png",intern=TRUE))
character(0)
> try(system("convert tmp/9c3bp1331157295.ps tmp/9c3bp1331157295.png",intern=TRUE))
character(0)
> try(system("convert tmp/1091wb1331157295.ps tmp/1091wb1331157295.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.319 0.676 3.999